{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "import os\n",
    "import os.path as osp\n",
    "import torch\n",
    "from torch_geometric.datasets import Planetoid"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [],
   "source": [
    "name='cora'\n",
    "root_path = '../'\n",
    "path = osp.join(root_path, 'data', name)\n",
    "dataset = Planetoid(path, name=name)\n",
    "data = dataset[0]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'torch_geometric.data.data.Data'>\n"
     ]
    }
   ],
   "source": [
    "print(type(data))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1: SparseTensor(row=tensor([   0,    0,    0,  ..., 2707, 2707, 2707]),\n",
      "             col=tensor([   0,  633, 1862,  ..., 1473, 2706, 2707]),\n",
      "             val=tensor([0.5000, 0.1667, 0.1443,  ..., 0.1250, 0.1250, 0.5000]),\n",
      "             size=(2708, 2708), nnz=13264, density=0.18%), 2: SparseTensor(row=tensor([   0,    0,    0,  ..., 2707, 2707, 2707]),\n",
      "             col=tensor([   0, 1862, 2582,  ..., 1473, 2706, 2707]),\n",
      "             val=tensor([0.3333, 0.3333, 0.3333,  ..., 0.2000, 0.1721, 0.3333]),\n",
      "             size=(2708, 2708), nnz=7158, density=0.10%)}\n"
     ]
    }
   ],
   "source": [
    "hl_path = osp.join('..\\\\data\\\\' + name + '\\\\HL_' + name + '_3.pt')\n",
    "HL2 = torch.load(hl_path)\n",
    "print(HL2)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[1.0000, 2.0000, 3.0000],\n",
      "        [7.0000, 0.0000, 1.2000]])\n"
     ]
    }
   ],
   "source": [
    "a = torch.tensor([[1,2,3],[7,0.0,1.2]])\n",
    "print(a)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[1., 1., 1.],\n",
      "        [1., 1., 1.]])\n"
     ]
    }
   ],
   "source": [
    "b = torch.ones(a.size())\n",
    "print(b)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[[1.0000, 2.0000, 3.0000],\n",
      "         [7.0000, 0.0000, 1.2000]],\n",
      "\n",
      "        [[1.0000, 1.0000, 1.0000],\n",
      "         [1.0000, 1.0000, 1.0000]]])\n",
      "torch.Size([2, 2, 3])\n",
      "tensor([[1.],\n",
      "        [1.],\n",
      "        [1.]])\n"
     ]
    }
   ],
   "source": [
    "z=[]\n",
    "z.append(a)\n",
    "z.append(b)\n",
    "c=torch.stack(z, dim=0)\n",
    "print(c)\n",
    "print(c.size())\n",
    "t = torch.ones(3,1)\n",
    "print(t)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[ 9.0000],\n",
      "        [11.2000]])\n"
     ]
    }
   ],
   "source": [
    "s=torch.einsum('bij,jk->ik', c,t )\n",
    "print(s)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "outputs": [
    {
     "data": {
      "text/plain": "tensor([[6.0000],\n        [8.2000]])"
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.mm(a,t)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[1.0000, 2.0000, 3.0000],\n",
      "        [7.0000, 0.0000, 1.2000]])\n",
      "[tensor([[1.0000, 2.0000, 3.0000],\n",
      "        [7.0000, 0.0000, 1.2000]]), tensor([[1.0000, 2.0000, 3.0000],\n",
      "        [7.0000, 0.0000, 1.2000]])]\n"
     ]
    }
   ],
   "source": [
    "print(a)\n",
    "t=[a,a]\n",
    "\n",
    "print(t)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "4\n",
      "6\n",
      "8\n"
     ]
    }
   ],
   "source": [
    "for i in range(2,10,2):\n",
    "    print(i)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.])\n"
     ]
    }
   ],
   "source": [
    "a = torch.Tensor(1)\n",
    "print(a)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "from collections import Counter\n",
    "\n",
    "def weisfeiler_lehman(graph, num_iterations=100):\n",
    "    # Assign initial colors to nodes based on their degrees\n",
    "    node_colors = {node: graph.degree(node) for node in graph.nodes}\n",
    "\n",
    "    # Perform WL iterations\n",
    "    for _ in range(num_iterations):\n",
    "        new_colors = {}\n",
    "        for node in graph.nodes:\n",
    "            # Get the colors of the neighbors\n",
    "            neighbor_colors = [node_colors[neighbor] for neighbor in graph.neighbors(node)]\n",
    "\n",
    "            # Combine the current node color with sorted neighbor colors\n",
    "            combined_colors = [node_colors[node]] + sorted(neighbor_colors)\n",
    "\n",
    "            # Create a color string and hash it\n",
    "            color_string = '_'.join(str(color) for color in combined_colors)\n",
    "            new_colors[node] = hash(color_string)\n",
    "\n",
    "        # Update the node colors\n",
    "        node_colors = new_colors\n",
    "        #print(node_colors)\n",
    "    print(node_colors)\n",
    "    return node_colors"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1: -1600003932409914981, 2: 8459395183220039833, 4: -6268908758547030116, 5: -2018854645855365795, 6: 9160304488943764732, 3: 3683494258503268398}\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Create a sample graph\n",
    "G = nx.Graph()\n",
    "edges = [(1,2),(1,4),(1,5),(1,6),(2,3),(3,4),(4,5),(5,6)]\n",
    "G.add_edges_from(edges)\n",
    "nx.draw(G,with_labels=True)\n",
    "\n",
    "# Apply the Welsh-Powell algorithm\n",
    "colors = weisfeiler_lehman(G)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{3: 4079612136336191393, 8: 4079612136336191393, 1: 4079612136336191393, 2: 4079612136336191393, 0: 4079612136336191393, 4: 4079612136336191393, 5: 4079612136336191393, 9: 4079612136336191393, 6: 4079612136336191393, 7: 4079612136336191393}\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "#random_graph = nx.gnp_random_graph(7, 0.4)\n",
    "random_graph = nx.random_graphs.random_regular_graph(3,10)  #生成包含10个节点、每个节点有2个邻居的规则图RG\n",
    "\n",
    "# Apply the Welsh-Powell algorithm\n",
    "colors = weisfeiler_lehman(random_graph,1000)\n",
    "# Draw the graph\n",
    "nx.draw(random_graph, with_labels=True, node_color='lightblue', edge_color='gray')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Draw the graph\n",
    "nx.draw(random_graph, with_labels=True, node_color='lightblue', edge_color='gray')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}